⚡️ Speed up function retry_with_backoff by 24%

[codeflash-ai]

📄 24% (0.24x) speedup for retry_with_backoff in code_to_optimize/code_directories/async_e2e/main.py

⏱️ Runtime : 1.05 milliseconds → 1.55 milliseconds (best of 246 runs)

📝 Explanation and details

The optimization achieves a 24.2% improvement in throughput (from 149,292 to 185,484 operations/second) by replacing the blocking time.sleep() call with the async-native await asyncio.sleep().

What changed:

• Imported asyncio module
• Replaced time.sleep(0.0001 * attempt) with await asyncio.sleep(0.0001 * attempt) on line 12

Why this improves throughput:
The key insight is that time.sleep() blocks the entire event loop, preventing any other concurrent tasks from executing during the backoff period. Even though individual retry attempts may take slightly longer (runtime increased from 1.05ms to 1.55ms), the async-native asyncio.sleep() yields control back to the event loop, allowing the system to process many more concurrent operations in parallel.

In async environments with concurrent workloads, this translates to significantly higher throughput because:

1. During each backoff period, instead of blocking, the event loop can now switch to processing other pending tasks
2. Multiple retry attempts across different concurrent calls can overlap their backoff periods
3. The system can maintain a steady flow of operations rather than getting blocked by each individual retry's sleep period

Impact on workloads:
This optimization is particularly beneficial for:

• High-concurrency scenarios (as shown in tests like test_retry_with_backoff_many_concurrent_successes with 50 concurrent tasks, and test_retry_with_backoff_throughput_high_volume with 500 tasks)
• Mixed success/failure patterns where multiple functions are retrying simultaneously with backoffs
• Any async application where retry_with_backoff is called concurrently from multiple coroutines

The trade-off of slightly slower individual execution (32% slower runtime per call) is more than compensated by the 24% throughput gain when processing multiple operations concurrently, which is the typical use case for async retry logic.

✅ Correctness verification report:

Test	Status
⚙️ Existing Unit Tests	🔘 None Found
🌀 Generated Regression Tests	✅ 754 Passed
⏪ Replay Tests	🔘 None Found
🔎 Concolic Coverage Tests	🔘 None Found
📊 Tests Coverage	100.0%

🌀 Click to see Generated Regression Tests

import asyncio  # used to run async functions

# function to test
# --- DO NOT MODIFY ---
import pytest  # used for our unit tests
from main import retry_with_backoff

# --- UNIT TESTS ---

# 1. Basic Test Cases


@pytest.mark.asyncio
async def test_retry_with_backoff_success_first_try():
    # Test that a function that succeeds immediately returns its value
    async def func():
        return "success"

    result = await retry_with_backoff(func)


@pytest.mark.asyncio
async def test_retry_with_backoff_success_second_try():
    # Test that a function that fails once then succeeds returns the correct value
    state = {"called": 0}

    async def func():
        state["called"] += 1
        if state["called"] == 1:
            raise ValueError("fail first")
        return "success"

    result = await retry_with_backoff(func)


@pytest.mark.asyncio
async def test_retry_with_backoff_max_retries_1_success():
    # Test with max_retries=1, should only try once
    async def func():
        return 42

    result = await retry_with_backoff(func, max_retries=1)


@pytest.mark.asyncio
async def test_retry_with_backoff_max_retries_1_failure():
    # Test with max_retries=1, should raise after first failure
    async def func():
        raise RuntimeError("fail always")

    with pytest.raises(RuntimeError, match="fail always"):
        await retry_with_backoff(func, max_retries=1)


# 2. Edge Test Cases


@pytest.mark.asyncio
async def test_retry_with_backoff_raises_valueerror_on_invalid_max_retries():
    # Test that function raises ValueError for invalid max_retries
    async def func():
        return "irrelevant"

    with pytest.raises(ValueError, match="max_retries must be at least 1"):
        await retry_with_backoff(func, max_retries=0)
    with pytest.raises(ValueError, match="max_retries must be at least 1"):
        await retry_with_backoff(func, max_retries=-5)


@pytest.mark.asyncio
async def test_retry_with_backoff_raises_original_exception_after_retries():
    # Test that the last exception is raised after all retries fail
    async def func():
        raise KeyError("always fails")

    with pytest.raises(KeyError, match="always fails"):
        await retry_with_backoff(func, max_retries=3)


@pytest.mark.asyncio
async def test_retry_with_backoff_preserves_exception_type():
    # Test that different exception types are preserved
    class CustomError(Exception):
        pass

    async def func():
        raise CustomError("custom fail")

    with pytest.raises(CustomError, match="custom fail"):
        await retry_with_backoff(func, max_retries=2)


@pytest.mark.asyncio
async def test_retry_with_backoff_async_func_returns_none():
    # Test that None is returned if the function returns None
    async def func():
        return None

    result = await retry_with_backoff(func)


# 3. Large Scale Test Cases


@pytest.mark.asyncio
async def test_retry_with_backoff_many_concurrent_successes():
    # Test many concurrent successful executions
    async def func(x):
        return x * x

    tasks = [retry_with_backoff(lambda x=x: func(x)) for x in range(50)]
    results = await asyncio.gather(*tasks)


@pytest.mark.asyncio
async def test_retry_with_backoff_many_concurrent_failures():
    # Test many concurrent failures, all should raise
    async def func():
        raise RuntimeError("fail")

    tasks = [retry_with_backoff(func, max_retries=2) for _ in range(20)]
    for task in tasks:
        with pytest.raises(RuntimeError, match="fail"):
            await task


@pytest.mark.asyncio
async def test_retry_with_backoff_mixed_concurrent():
    # Test a mix of successes and failures concurrently
    async def func_success(x):
        return x

    async def func_fail():
        raise ValueError("fail")

    tasks = [retry_with_backoff(lambda x=x: func_success(x)) for x in range(10)] + [
        retry_with_backoff(func_fail) for _ in range(5)
    ]
    results = []
    for i, task in enumerate(tasks):
        if i < 10:
            res = await task
            results.append(res)
        else:
            with pytest.raises(ValueError, match="fail"):
                await task


# 4. Throughput Test Cases


@pytest.mark.asyncio
async def test_retry_with_backoff_throughput_small_load():
    # Test throughput with a small number of concurrent tasks
    async def func(x):
        return x + 1

    tasks = [retry_with_backoff(lambda x=x: func(x)) for x in range(10)]
    results = await asyncio.gather(*tasks)


@pytest.mark.asyncio
async def test_retry_with_backoff_throughput_medium_load():
    # Test throughput with a medium number of concurrent tasks
    async def func(x):
        return x * 2

    tasks = [retry_with_backoff(lambda x=x: func(x)) for x in range(100)]
    results = await asyncio.gather(*tasks)


@pytest.mark.asyncio
async def test_retry_with_backoff_throughput_high_volume():
    # Test throughput with a higher number of concurrent tasks, but under 1000
    async def func(x):
        return x - 1

    tasks = [retry_with_backoff(lambda x=x: func(x)) for x in range(500)]
    results = await asyncio.gather(*tasks)


@pytest.mark.asyncio
async def test_retry_with_backoff_throughput_with_failures_and_successes():
    # Test throughput with a mix of successes and failures
    async def func(x):
        if x % 10 == 0:
            raise RuntimeError(f"fail {x}")
        return x

    tasks = [retry_with_backoff(lambda x=x: func(x), max_retries=2) for x in range(50)]
    for i, task in enumerate(tasks):
        if i % 10 == 0:
            with pytest.raises(RuntimeError, match=f"fail {i}"):
                await task
        else:
            res = await task


# codeflash_output is used to check that the output of the original code is the same as that of the optimized code.

To edit these changes git checkout codeflash/optimize-retry_with_backoff-mk53lel6 and push.